AbstractA Coupled Cloud and Snow Detection Algorithm (CCSDA) has been developed (part 1: Li et al. (2007)) for improving current satellite capabilities to estimate downward surface short-wave radiation (DSSR) under snow conditions. The algorithm is based on observations from four channels of the GOES-8 imager and is used to detect clouds, snow, and perform clear-sky background analysis. It has been applied to 1 year (1997) of pixel level satellite observations over the United States to obtain inputs for the DSSR inference scheme. When compared to results from earlier model outputs, the surface short-wave fluxes have significantly improved for the snow situation, and resulting estimates of snow extent compare well with independent snow products. Evaluation of improvements in snow detection and DSSR fluxes will be presented and discussed.